Research Of Case-Based Reasoning Technique On Monitoring And Controlling Drilling Complexities Based On Ontology

Drilling Engineering is a hidden underground project, so there is a lot of ambiguity, randomness and uncertainty in the entire drilling process which often lead to many complexities, enormous amount of resource and time consuming, even causing huge economic loses. In order to improve the decision making level of diagnosis, prevention and treatment on drilling complexities, this research carried out the study of Case-Based Reasoning Technique on monitoring and controlling drilling complexities ontology-based of based on knowledge ontology and problem-solving approach, from the perspective of knowledge systems. And the performance reflected the following four main aspects:Firstly, establishing intelligent decision system model and knowledge model of monitoring and controlling drilling complexities based on ontology, and constructing in detail of the task ontology, concept ontology and method ontology of monitoring and controlling of drilling complexities; Secondly, considering the scalability of knowledge, this research proposed cyclic evolution of law and protege tools to build knowledge ontology on monitoring and controlling of drilling complexities and gave details of their implementation process; Thirdly, putting forward knowledge representation of Web Ontology Language (owl) and the storage method of how ontology forming knowledge base; using ontology analysis tool Jena to achieve semantic query; Applying depth-first, breadth-first algorithm, similarity calculation and case based reasoning in decision-making analysis and building the neural network ontology model; Finally, implementing Web-based system, using Eclipse as a development platform, Mysql database, Web server Tomcat and JSP technology. The development of monitoring and controlling of drilling complexities based on ontology for intelligent decision-making system overcomes the bottlenecks of traditional reasoning of knowledge acquisition, improves the integration of knowledge and levels of knowledge sharing and reusing, has a good inheritance, easy to expand and maintain, lays a foundation for further study.